This paper describes a simple educational simulation tool to teach about agent-based modeling (ABM) and land use and transportation (LUT) interactions in urbanized regions. The relationship between land use and transportation in urban areas shows a dynamic complexity which is difficult to model with static or very aggregated approaches. Agent-based simulation is becoming a standard to model certain complex systems including LUT interactions. The LUT modeling with agent-based simulation has been evolving in the last 20 years and there are some complete models being applied to real metropolitan areas. In this paper, only some of the ingredients of those models are presented in an easy to explain agent-based model that can be used in classes.

We consider time critical supply chains in the Australia dairy industry and re-covery policies in the presence of the ripple effect. Ripple effect is the impact of a dis-ruption on supply chain economic performance and disruption-based scope of changes needed in the supply structures and parameters to preserve the resilience. First, we de-scribe the ripple effect in general and one example of the ripple effect in the dairy supply chain in Australia. Second, we present a model for reactive recovery policies in the dairy supply chain under conditions of the ripple effect and exemplify them on a simulation example. The results of this study can be used in future for comparing proactive and re-active approaches to tackling the ripple effect from resilience and flexibility views.

Sourcing strategy analysis in the settings of supply chain flexibility in regard to single vs dual sourcing has been a well explored area over the last two decades. In recent years, single vs dual sourcing analy-sis has been increasingly introduced in supply chain disruption management. Since most of the deci-sion-support models for supply chain sourcing strategy adaptation in the case of disruptions presume real-time information and coordination, the issues of Big Data and business intelligence needs to be included into the consideration. A supply chain simulation model with consideration of capacity dis-ruption and Big Data along with experimental results are presented. Based on both literature analysis and modelling example, managerial insights are derived. A set of sensitivity experiments allows to illustrate the model’s behaviour. The analysis suggest recommendation on using single sourcing, ca-pacity flexibility, and dual sourcing for different combinations of demand and inventory patterns. The paper is concluded by summarizing the most important insights and outlining future research agenda.

In light of low-frequency/high-impact disruptions, the ripple effect has recently been intro-duced into academic literature on supply chain management. The ripple effect in the supply chain results from disruption propagation from the initial disruption point to the supply, pro-duction and distribution networks. While optimization modelling dominates this research field, the potential of simulation modelling still remains under-explored. The objective of this study is to reveal research gaps that can be closed with the help of simulation modelling.

The recently adopted Sustainable Development Goals call for the end of poverty and the equitable provision of healthcare. These goals are often at odds, however: health seeking can lead to catastrophic spending, an outcome for which cancer patients and the poor in resource-limited settings are at particularly high risk. How various health policies affect the additional aims of financial wellbeing and equity is poorly understood. This paper evaluates the health, financial, and equity impacts of governmental and charitable policies for surgical oncology in a resource-limited setting. Three charitable platforms for surgical oncology delivery in Uganda were compared to six governmental policies aimed at improving healthcare access. An extended cost-effectiveness analysis using an agent-based simulation model examined the numbers of lives saved, catastrophic expenditure averted, impoverishment averted, costs, and the distribution of benefits across the wealth spectrum.

Sortie Generation Rate (SGR) is an important metric for air dominance. Lockheed Martin must demonstrate that the Air System can fly the sorties during an allotted time and deliver the capability to the war fighter. Aircraft turnaround time- the time between when the aircraft touches down, refuels, rearms, and completes inspections in order to release the aircraft, to aircraft wheels up - plays an important role in achieving the SGR requirement.

Pertussis control remains a challenge due to recently observed effects of waning immunity to acellular vaccine and suboptimal vaccine coverage. Multiple outbreaks have been reported in different ages worldwide. For certain outbreaks, publichealth authorities can launch an outbreak response immunization (ORI) campaign to control pertussis spread. The authors developed an agent-based model to investigate effects of outbreak response immunization campaigns targeting young adolescents in averting pertussis cases. The experience proved that ABM offers a promising methodology to evaluate other public health interventions used in pertussis control. The authors also identified the strong need for further research into application of modeling to further our understanding of pertussis epidemiology.

The public assistance system is supposed to offer a bridge between poverty and self-sufficiency. Families receive benefits such as Temporary Assistance for Needy Families (TANF) or Supplemental Nutrition Assistance Program (SNAP) to soften the impact of loss of income. The programs are intended to be limited in duration and provide a very modest amount of financial support. Some families are fortunate to also receive a housing voucher or a child care subsidy to help offset basic expenses. Eligibility for benefits varies by program and is based on different criteria, most of which are linked to personal income. This study asks: what happens when benefits are cut before individuals reach economic stability? This is frequently called the “benefits cliff.”

Order picking is one of the most labor- and time-consuming processes in supply chains. Improving the performance of order picking is thus a frequently researched topic. Due to high cost pressure for warehouse managers the space in storage areas has to be used efficiently. Hence narrow-aisle warehouses where order pickers cannot pass as well as several order pickers working in the same area are common. This leads to congestion which is in this context referred to as picker blocking. This paper employs an agent-based simulation approach to investigate the effects of picker blocking in manual order picking systems with different combinations of routing policies for three order pickers in a rectangular warehouse with narrow-aisles.

Spare part management is essential to many organizations, since excess inventory leads to high holding costs and stock outs can greatly impact operations performance, but it is a major problem in the testing work shop in Robert Bosch China Diesel (RBCD) Wuxi. The workshop is used to test the functionality of the injectors, such as those statistics for pressure, electro conductivity, etc. After implementing the automated tower storage in the work shop, the workshop supervisor applied monthly order policy to purchase spare parts, which means at the end of each month, he/she will check the consumption of last month’s spare parts and make orders according to that data. However, in order to control the inventory of spare parts and achieve minimum total inventory cost of those parts, the (Q, r) model was suggested to make the monthly order, realizing the goal of maximizing the net profit of injectors.